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This repository serves as a comprehensive resource hosting data and detailed instructions related to the experiments conducted for the paper titled "Mining Frequent Structures in Conceptual Models", ubject to peer review in the "Data Mining and Knowledge Discovery" journal.

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CM-Mining Application - Experimental Instructions

This README provides instructions for conducting experiments and demonstrations using the CM-Mining application. Please refer to the paper "Mining Frequent Structures in Conceptual Models" (under review) for additional details, specifically sections 6 and 7.

Installation

  1. Visit CM-Mining GitHub Repository.
  2. Follow the installation instructions provided in the repository to install the application.

Experiment Instructions

Experiment 1

  1. Copy the models folder into the application root folder.
  2. Run each of the 6 trials discussed in the paper by applying the parameters specified in the parameters.txt file.

Experiment 2

  1. Copy the models folder into the application root folder.
  2. Run the two trials (first with 47 models, second with 94) by executing the test.py file.
    • Use the nodes and frequency parameters described in the corresponding experiment section (refer to Table 3).
    • Generate a performance report using: python3 -m cProfile test.py > test.txt.

Experiment 3

  1. Run test_confusionmatrix.py to generate the data discussed in the corresponding section.
  2. The outputpatterns.txt file represents the list of patterns to be clustered.

Demonstration

This section provides a complete set of models and 5 trials used to generate the list of patterns.

  • Each trial folder contains:
    • Parameters used
    • Generated graphs
    • Generated patterns

Feel free to explore these folders to understand the experiments conducted and the outcomes achieved.

For any further details or inquiries, refer to the paper's Sections 6 and 7 or consult the repository's documentation.

Note

Ensure the application is set up correctly and all dependencies are installed before executing the experiments or demonstrations.

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This repository serves as a comprehensive resource hosting data and detailed instructions related to the experiments conducted for the paper titled "Mining Frequent Structures in Conceptual Models", ubject to peer review in the "Data Mining and Knowledge Discovery" journal.

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